In this paper, we propose a novel input device for a robotic prosthetic hand based on capacitance change. The proposed device can sense the deformation of the skin due to the activity of the muscle by measuring the capacitance change between the skin and the electrode. Therefore, it can be used as a sensor for estimating a user's intention through medical electrodiagnostic techniques such as electromyogram (EMG)and force myography (FMG). The proposed device can acquire data in a non-invasive way and is advantageous with easier data processing than that for an EMG signal. Moreover, it is resistant to the impedance change of skin because the capacitance is measured in a non-contact manner, unlike the existing methods which work with direct contact with the skin such as EMG. Additionally, unlike FMG, the device is lightly attached to the skin without being strongly fixed with velcro, which offsets problems that occur while re-wearing the device. To demonstrate the feasibility of the proposed idea, three of the newly developed input devices were used to classify four hand movements (fist, scissors, paper, and rest)using a multilayer perceptron (MLP). As a result, the classification success rates for the fist, paper, scissor, and rest motions were obtained as 99.3%, 98.3%, 98.4%, and 99.1%, respectively.

This paper presents a grasping force-feedback user interface (GFUI) which transfers the accurate kinesthetic force detected during robot-assisted minimally invasive surgery (RMIS) to a user, and allows the users to perform grasping motions with articulation and intuition. Using the GFUI, a developed robot hardware (S-surge) is controlled, and the force data measured from the robot are reflected to the GFUI. To evaluate the effect of grasping force-feedback control using the GFUI, a group of subjects (n=10) participated in a standard peg transfer tasks with and without the feedback control. To conduct the tasks, a developed robot hardware and a commercial haptic device were used which make the entire surgical environment including the GFUI as a master-slave controlled system. As a result, the performance of the GFUI was verified through the conducted tasks using the entire surgical system.

This paper presents a novel surgical instrument integrated with a four-degree-of-freedom (DOF) force sensor. By adopting the capacitive transduction principle, the sensor enables the direct sensing of normal and shear forces at surgical instrument tips. Thus, three-DOF pulling forces and a single-DOF grasping force can be measured for haptic feedback control of robotic minimally invasive surgery systems. The sensor consists of four capacitive transducers, and all the transducers including analog signal processing units are embedded in small surgical instrument tips. The four-DOF force sensing is enabled thanks to the four capacitive transducers by using the force transformation method. In this study, the instrument is designed and manufactured to be adaptable to the open-source surgical robot platform, called Raven-II. In addition, the sensing system is experimentally validated through its application to the Raven-II by using a reference force sensor.

This paper presents a grasper-integrated force sensor that provides the capability of measuring dual axial forces at the tip of surgical robot for minimally invasive surgery (MIS). On the sensorized forceps, the combination of dual axial forces measured at each side of grasper presents three axial pulling and single axial grasping force sensing, which provide force feedback control using haptic device. It consists of simple structure of triangular prism shape and two capacitive-type pressure sensor cells based on elastomeric polymer which provides the information on normal and shear forces. The sensing principle is to compare the difference between responses of two pressure sensors when the surface of the sensor contacts to the tissue. A sensorized forceps is fabricated by employing the molding method and electronics for signal processing is embedded. Finally, experimental evaluations are performed and its feasibility is validated.

This paper presents a multi-axial force sensing system for haptic feedback of minimally invasive robotic surgery. The system consists of a 3-axial force sensor located on the wrist of surgical grasper and a torque sensor which plays a role of pulley for driving tendons. The 3-axial force sensor measures magnitude and direction of manipulation forces when the grasper grasps and pulls the tissue, while the torque sensor measures grasping force transferred through the driving tendons. The sensors and a grasper mechanism are designed and manufactured. For the calibration and verification of the prototype sensors, a testbed which simulates tissue manipulation is built and experiments are performed to evaluate the sensing system.

This paper presents a preliminary design and experimental results of a multi-axial contact force sensor for robotic surgery graspers. The sensor is a thin-film type capacitive one with a multiple cell structure capable of measuring normal and shear forces at contacts simultaneously. The structure of the sensor is determined via numerical optimization for maximizing sensitivity and based on the results, a prototype is fabricated by employing the silk-screening method. The characteristics of the sensor are evaluated with a multi-axial sensor calibration set-up and the sensitivities for two directional shear forces and a normal forces are measured to be 10.1, 10.3 and 6.1%, respectively. In this study, the feasibility of the sensor is confirmed as the proof-of-concept. In our future studies, a miniaturized pair of the proposed sensor will be embedded to a surgery grasper for in vitro validation.

In this paper, we present a smart handheld surgical tool with tactile feedback to help microsurgery. This device consists of force sensors attached to the tool tip and tactile displays on the position of the fingerhold. The sensor is capacitive one and measures not only the magnitude of force, but also the direction of force. The sensor can measure 9N of lateral forces along x-y-z direction. The tactile display is based on dielectric elastomer actuators and made up of three rigid coupling tactile display modules. The tactile displays provide stimuli of 170μm displacement and frequency of 10Hz at the surgeons fingertips. We fabricate the device and its performances are experimentally validated.

In this paper, we present the autonomous pipeline navigation method of an in-pipe robot, based on the landmark recognition system and 3D orientation sensor. The fittings of pipelines such as elbows and branches can be used as the landmarks. In this paper, we introduce a noise tolerant landmark detection method using a line laser beam projected on the internal surface of the pipeline. Once the line laser is projected on the surface of landmarks, a unique line pattern is generated. By using this line pattern, the robot can easily detect and distinguish these landmarks while recognizing the direction of the pipeline path. Simultaneously, the robot's pose information from the orientation sensor and the driving motor's encoder is continuously recorded and used to reconstruct a map of the pipelines. By using this map and a specific navigation strategy, the robot can navigate in the 3D pipeline autonomously. The effectiveness of the proposed method is validated by experiments using the in-pipe robot called MRINSPECT V.

System virtualization is now available for mobile devices allowing for many advantages. Two of the major benefits from virtualization are system fault isolation and security. The isolated driver domain (IDD) model, a widely adopted architecture, enables strong system fault isolation by limiting the impact of driver faults to the driver domain itself. However, excessive I/O requests from a malicious domain to an IDD can cause CPU overuse of the IDD and performance degradation of applications in the IDD and other domains that share the same I/O device with the malicious do-main. If the IDD model is applied to mobile devices, this failure of performance isolation could also lead to battery drain, and thus it introduces a new severe threat to mobile devices. In order to solve this problem, we propose a fine-grained I/O access control mechanism in an IDD. Requests from guest domains are managed by an accounting module in terms of CPU usage, with the calcula-tion of estimated CPU consumption using regression equations. The requests are scheduled by an I/O access control enforcer ac-cording to security policies. As a result, our mechanism provides precise control on the CPU usage of a guest domain due to I/O device access, and prevents malicious guest domains from CPU overuse, performance degradation, and battery drain. We have implemented a prototype of our approach considering both network and storage devices with a real smart phone (SGH-i780) that runs two para-virtualized Linux kernels on top of Secure Xen on ARM. The evaluation shows our approach effectively protects a smart phone against excessive I/O attacks and guarantees availability.